# Staff Engineer - Content Intelligence Infrastructure

**Company:** [Spotify](https://hotfix.jobs/companies/spotify)
**Location:** London, United Kingdom, Stockholm, Sweden
**Role:** ML Engineering
**Experience:** 7+ years
**Skills:** Java, Python, Scala, Distributed Systems, ML Infrastructure, Backend Systems, Data Processing, LLMs, AI, Multimodal Processing, Search Infrastructure, Recommendation Systems, Audio Processing, Real-Time Systems, Content Enrichment
**Posted:** 2026-05-28

> Staff Engineer leading foundational backend, distributed data, and ML infrastructure for Spotify’s multimodal content intelligence systems. The role requires extensive large-scale systems experience, strong Java, Python, or Scala skills, and experience delivering AI- and LLM-enabled products.

## Job Description

## Responsibilities
- Lead the design and evolution of data, backend, and ML infrastructure systems for content intelligence.
- Build scalable infrastructure for multimodal processing across audio, video, text, and images.
- Partner with product managers, engineering managers, and senior engineers on technical strategy.
- Drive architecture across distributed systems, ML infrastructure, data processing platforms, and reliability.
- Improve AI- and LLM-enabled workflows, including transcript processing, metadata enrichment, and content understanding.
- Develop reliable, cost-efficient systems for high-throughput processing and real-time intelligence.
- Collaborate across organizational boundaries to drive alignment and long-term platform investments.
- Mentor engineers and raise engineering standards.

## Requirements
- Extensive experience building and scaling large-scale backend and infrastructure systems in distributed environments.
- Strong technical judgment balancing scalability, reliability, cost, and product needs.
- Strong programming experience in Java, Python, and/or Scala.
- Understanding of high-volume multimedia or real-time workloads.
- Experience building products using AI and LLMs at large scale, including quality and cost trade-offs.
- Ability to operate in ambiguous environments and shape technical direction.
- Effective communication across engineering, product, and leadership stakeholders.
- Experience leading complex initiatives across multiple teams or organizational areas.
- Commitment to collaboration, mentorship, and cross-team alignment.

## Nice to Have
- Exposure to search infrastructure, recommendation systems, or audio processing systems.
- Experience in startup environments or early-stage product areas.

## Work Arrangement
- Based in London or Stockholm.
- Hybrid flexibility with some in-person meetings and the option to work from home.

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